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Section: aic
Surface Defect Detection using Convolutional Neural Network Model Architecture
by Sohail Shaikh, Deepak Hujare and Shrikant Yadav
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 134-144, 2022; DOI: 10.55708/js0105014
Abstract: With the dominance of a technical and volatile environment with enormous consumer demands, this study aims to investigate the advancements in quality assurance in the era of Industry 4.0. For better production efficiency, rapid and robust automated quality visual inspection is developing rapidly in product quality control. Deep neural network architecture is built for a… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Machine Learning Aided Depression Detection in Community Dwellers
by Vijay Kumar, Muskan Khajuria and Anshu Singh
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 17-24, 2022; DOI: 10.55708/js0105002
Abstract: Depression is a mental condition that can have serious negative effects on an individual’s thoughts and nd health problems that could lead to grave heart diseases. Depression detection has become necessary in community dwellers considering the lifestyle being followed. Here we use NHANES dataset to compare the performance of various machine learning algorithms in depression… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Evolutionary Learning of Fuzzy Rules and Application to Forecasting Environmental Impact on Plant Growth
by Chris Nikolopoulos and Ryan Koralik
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 48-53, 2022; DOI: 10.55708/js0104006
Abstract: Prediction of plant growth and yield is one of the essential tasks that enables growers of food and agricultural products to effectively manage their crops. In this paper, a hybrid evolutionary/fuzzy machine learning approach is introduced where a genetic algorithm is deployed to learn the optimum membership functions of relevant fuzzy sets and a knowledge… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Bearing Fault Diagnosis Based on Ensemble Depth Explainable Encoder Classification Model with Arithmetic Optimized Tuning
by Kaibi Zhang, Yanyan Wang and Hongchun Qu
Journal of Engineering Research and Sciences, Volume 1, Issue 3, Page # 81-97, 2022; DOI: 10.55708/js0103009
Abstract: In a dynamic and complex bearing operating environment, current auto-encoder-based deep models for fault diagnosis are having difficulties in adaptation, which usually leads to a decline in accuracy. Besides, the opaqueness of the decision process by such deep models might reduce the reliability of the diagnostic results, which is not conducive to the subsequent optimization… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Artificial Intelligence – Computer Science (AIC))
Neural Networks and Digital Arts: Some Reflections
by Rômulo Augusto Vieira Costa and Flávio Luiz Schiavoni
Journal of Engineering Research and Sciences, Volume 1, Issue 1, Page # 10-18, 2022; DOI: 10.55708/js0101002
Abstract: The Constant advancement in the area of machine learning has unified some areas that until then di a of computing with the arts in general. With the emergence of digital art, people have become increasingly interested in the development of expressive techniques and algorithms for creating works of art, whether in the form of music,… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Artificial Intelligence – Computer Science (AIC))